Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/102927
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Building Environment and Energy Engineering | en_US |
| dc.creator | Du, Y | en_US |
| dc.creator | Mak, CM | en_US |
| dc.creator | Li, Y | en_US |
| dc.date.accessioned | 2023-11-17T02:58:50Z | - |
| dc.date.available | 2023-11-17T02:58:50Z | - |
| dc.identifier.issn | 0360-1323 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10397/102927 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Pergamon Press | en_US |
| dc.rights | © 2018 Elsevier Ltd. All rights reserved. | en_US |
| dc.rights | © 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/. | en_US |
| dc.rights | The following publication Du, Y., Mak, C. M., & Li, Y. (2018). Application of a multi-variable optimization method to determine lift-up design for optimum wind comfort. Building and Environment, 131, 242-254 is available at https://doi.org/10.1016/j.buildenv.2018.01.012. | en_US |
| dc.subject | Computational fluid dynamics (CFD) | en_US |
| dc.subject | Lift-up design | en_US |
| dc.subject | Multi-variable optimization method | en_US |
| dc.subject | Response surface methodology (RSM) | en_US |
| dc.subject | Wind comfort | en_US |
| dc.title | Application of a multi-variable optimization method to determine lift-up design for optimum wind comfort | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.spage | 242 | en_US |
| dc.identifier.epage | 254 | en_US |
| dc.identifier.volume | 131 | en_US |
| dc.identifier.doi | 10.1016/j.buildenv.2018.01.012 | en_US |
| dcterms.abstract | The lift-up building design has been demonstrated to provide favorable wind comfort, but there is a lack of investigation on optimum wind comfort condition. This study coupled computational fluid dynamics (CFD) technique and response surface methodology (RSM) to determine the most desirable wind comfort around an isolated building with lift-up design. A multi-variable optimization method is proposed to determine optimum wind comfort and the corresponding lift-up design variables, namely, lift-up height (HL), core aspect ratio (AR) and core number (N). To better illustrate wind comfort around the building, the wind comfort in the lift-up area and the podium area are investigated separately. The Detached Eddy Simulation (DES) approach is employed throughout the whole CFD simulation process. The quality and goodness of the established RSM models are examined by analysis of variance and genetic algorithm is applied to generate optimal design solution. The generated results illustrate good performance of the established RSM model. Results show that the optimum wind comfort is obtained when HL is 8 m, AR is 10%, and N is 6. The lift-up core aspect ratio is subsequently found to have greatest effect on wind comfort among the three design variables in both the lift-up area and the podium area. In addition, the proposed method is applicable to other similar environmental design conditions and the outcomes of study can also be of great value in the improvement of wind comfort in compact urban cities. | en_US |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Building and environment, Mar. 2018, v. 131, p. 242-254 | en_US |
| dcterms.isPartOf | Building and environment | en_US |
| dcterms.issued | 2018-03 | - |
| dc.identifier.scopus | 2-s2.0-85044379287 | - |
| dc.identifier.eissn | 1873-684X | en_US |
| dc.description.validate | 202310 bckw | en_US |
| dc.description.oa | Accepted Manuscript | en_US |
| dc.identifier.FolderNumber | BEEE-0517 | - |
| dc.description.fundingSource | RGC | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.identifier.OPUS | 6830083 | - |
| dc.description.oaCategory | Green (AAM) | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Du_Application_Multi-Variable_Optimization.pdf | Pre-Published version | 1.84 MB | Adobe PDF | View/Open |
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